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首页> 外文期刊>The Journal of Strain Analysis for Engineering Design >Measuring the mechanical properties of human skin in vivo using digital image correlation and finite element modelling
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Measuring the mechanical properties of human skin in vivo using digital image correlation and finite element modelling

机译:使用数字图像关联和有限元建模测量体内人体皮肤的机械性能

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摘要

The mechanical properties of the skin are important in many applications, but are not well understood. This paper presents a method for measuring the mechanical properties of human skin in vivo using digital image correlation, with a finite element model that was used to optimize the material properties to obtain the best match with the model data. The skin was modelled as an Ogden hyperelastic membrane, with a tension field wrinkling model and an initial stretch identified as an additional material parameter, and the boundary conditions were the measured load and the displacements around the edge of the region of interest. Fast, reliable convergence was obtained using a Hager–Zhang non-linear conjugate gradient solver. A stochastic optimization procedure was used to identify the material parameters. Good estimates of the material parameters could be obtained from the displacement field at a single time point. Typical material parameters were μ = 10 Pa, α = 26, and an initial strain of 0.2. These parameters were not unique; the stochastic optimization procedure gave good global convergence and an indication of the overall uncertainty in the identification of the results. It is argued that the use of the DIC technique, which generates very large amounts of data, also gave a clearer picture of the overall uncertainty.
机译:皮肤的机械性能在许多应用中很重要,但尚未被很好地理解。本文提出了一种使用数字图像相关技术测量人体皮肤体内机械性能的方法,该方法具有有限元模型,该模型用于优化材料性能以获得与模型数据的最佳匹配。将皮肤建模为Ogden超弹性膜,并使用张力场起皱模型和初始拉伸作为附加材料参数,并且边界条件是所测得的载荷和目标区域边缘附近的位移。使用Hager-Zhang非线性共轭梯度求解器可以获得快速,可靠的收敛。随机优化程序用于确定材料参数。可以从单个时间点的位移场获得材料参数的良好估计。典型的材料参数为μ= 10 Pa,α= 26,初始应变为0.2。这些参数不是唯一的。随机优化程序具有良好的全局收敛性,并表明了结果识别的总体不确定性。有人认为,使用DIC技术可产生大量数据,这也使整体不确定性的情况更加清晰。

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